Nvidia has unveiled a new artificial intelligence model, Nemotron-4-Mini-Hindi-4B, specifically tailored for the Hindi language and its dialects in India. The model is optimised for Nvidia’s GPU, features four billion parameters, and is available through Nvidia NIM microservices.
It also marks the company’s first foray into creating language models specifically for India’s widely spoken languages.
Nvidia revealed that the model was developed through pruning, distillation, and training on a combination of real-world Hindi data, synthetic Hindi data, and English data. This balanced data approach ensures the model can have linguistic and cultural nuances.
“By integrating English data into the training, we’ve equipped the model to work effectively in India’s diverse, multilingual environment, bridging gaps where bilingualism comes into play,” Nvidia stated.
Nvidia’s focus on Hindi sets the stage for more localised AI solutions. Unlike the large language models, such as OpenAI’s GPT-4, Nemotron-4-Mini-Hindi-4B is a smaller, more targeted model. Smaller language models are cheaper to train and deploy, making them attractive to businesses that may not have the resources to invest in massive AI infrastructure.
One of India’s largest IT services firms, Tech Mahindra, has already integrated Nvidia’s new model into its operations. The company has developed Indus 2.0, an AI platform based on Hindi and regional dialects. The platform aims to enhance services like customer support, content translation, and other language-dependent applications.
Nvidia’s chief executive, Jensen Huang, also met and shared the stage with Mukesh Ambani, chairman of Reliance Industries at the Nvidia AI Summit in Mumbai
This move also aligns with the growing interest of the global semiconductor industry in India. Over the past few years, companies like Nvidia have ramped up their investments in the country, viewing it as a future powerhouse in the AI and semiconductor sectors.
While India has a long road ahead to compete with established semiconductor hubs like Taiwan, small steps like this are crucial.
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